Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
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DOI：
10.1142/3774
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发表时间：
1999-02
期刊：
影响因子：
--
通讯作者：
S. Ge;Tong-heng Lee;C. Harris
中科院分区：
文献类型：
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作者：
S. Ge;Tong-heng Lee;C. Harris
机器人的神经网络控制已经引起了相当大的研究兴趣，并且在解决与机器人控制问题有关的一些特殊问题时已经取得了令人满意的结果。本文致力于基于神经网络的机器人自适应控制问题。文本已定制给机器人动力学的全面研究，目前结构化的网络模型的机器人，并提供系统的方法，基于神经网络的自适应控制器设计的刚性机器人，柔性关节机器人，和机器人在约束运动。严格证明的自适应神经网络控制器的稳定性。仿真例子也验证了控制器的有效性，并与控制器的实际实现问题进行了讨论。
There has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an "on-and-off" fasion. This text is dedicated to issues on adaptive control of robots based on neural networks. The text has been tailored to give a comprehensive study of robot dynamics, present structured network models for robots, and provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.